Global Positioning System (GPS) becomes one of the key technologies in precise navigation and position area. Interference Suppression technology of GPS plays an essential role in the accuracy of GPS positioning. In this paper, we proposed a more efficient scheme based on Gram-Schmidt algorithm with the training sequence, which is named the GSCE algorithm(the Gram-Schmidt Channel estimation algorithm). Compared with some other existing methods, the algorithm improves the positioning precision of the GPS by estimating channel parameters.

Global Navigation Satellite System (GNSS) signal simulator plays an important role in designing navigation signal and developing receiver. Traditional GNSS signal simulators are almost implemented based on the combination of software and hardware whereas they are usually complex and costly. In this paper, a GNSS signal simulator is designed based on Digital Signal Processor (DSP) and Field Programmable Gate Array (FPGA). The computation of signal parameters and generation of signal are both implemented in hardware. After the GNSS signal model is presented, the structure of the simulator and the function of each part are introduced. Then the frequency scheme used in system is analyzed. Finally, the generation procedures of primary Pseudo Random Noise (PRN) code, secondary PRN code, navigation data and the method of chip shaping are illuminated in detail.

By making use of the characteristic of the cost function MSSO (Mean of the Square Soft Outputs), a new method of carrier phase synchronization and decoding for the turbo-coded systems is presented. Firstly, a short training sequence is used to achieve the initial phase estimation and to narrow the phase searching range. Secondly, three decoding sequences with the largest MSSO values are chosen by means of parallel searching strategy. Furthermore, the three selected decoding sequences are finally processed according to the majority decision criterion. The proposed method does not have to iteratively estimate and correct the carrier phase to get the desired synchronization. The calculation is greatly reduced though the transmission efficiency will be sacrificed a little in the presence of the training sequence.